Merge pull request #17 from phydrus/dev

Update ci.yml

.github/workflows/ci.yml

@@ -0,0 +1,41 @@
+name: codacy-coverage-reporter
+
+on: 
+  push:
+    branches: 
+      - master
+  pull_request:
+    branches: 
+      - master
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.7, 3.8, 3.9]
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+          pip install codacy-coverage
+          pip install coverage
+          pip install -e .
+      
+      - name: Test with unittest
+        run: |
+          coverage run -m unittest discover
+          coverage xml
+          
+      - name: Run codacy-coverage-reporter
+        uses: codacy/codacy-coverage-reporter-action@master
+        with:
+          project-token: ${{ secrets.CODACY_PROJECT_TOKEN }}
+          coverage-reports: coverage.xml

joss_paper/paper.bib

@@ -27,6 +27,7 @@ @article{priestley1972assessment
   number={2},
   pages={81--92},
   year={1972}
+  doi={10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2},
 }
 
 @article{wright1982new,
@@ -47,7 +48,8 @@ @article{thom1977penman
   number={436},
   pages={345--357},
   year={1977},
-  publisher={Wiley Online Library}
+  publisher={Wiley Online Library},
+  doi={10.1002/qj.49710343610},
 }
 
 @article{thornthwaite1948approach,
@@ -59,6 +61,7 @@ @article{thornthwaite1948approach
   pages={55--94},
   year={1948},
   publisher={JSTOR}
+  doi={10.2307/210739},
 }
 
 @article{blaney1952determining,
@@ -86,7 +89,7 @@ @article{xu2001evaluation
 number = {2},
 pages = {305-319},
 keywords = {evaporation, temperature-based methods, north-western Ontario},
-doi = {https://doi.org/10.1002/hyp.119},
+doi = {10.1002/hyp.119},
 url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.119},
 eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.119},
 abstract = {Abstract Seven temperature-based equations, each representing a typical form, were evaluated and compared for determining evaporation at two climatological stations (Rawson Lake and Atikokan) in north-western Ontario, Canada. The comparison was first made using the original constant values involved in each equation, and then using the recalibrated constant values. The results show that when the original constant values were used, larger biases existed for most of the equations for both stations. When recalibrated constant values were substituted for the original constant values, six of the seven equations improved for both stations. Using locally calibrated parameter values, all seven equations worked well for determining mean seasonal evaporation values. For monthly evaporation values, the modified Blaney–Criddle method produced least error for all months for both stations, followed by the Hargreaves and Thornthwaite methods. The Linacre, Kharrufa and Hamon methods showed a significant bias in September for both stations. With properly determined constant values, the modified Blaney–Criddle, the Hargreaves and Thornthwaite methods can be recommended for estimating evaporation in the study region, as far as temperature-based methods are concerned. Copyright © 2001 John Wiley \& Sons, Ltd.},
@@ -101,7 +104,7 @@ @article{xu2000evaluation
 number = {2},
 pages = {339-349},
 keywords = {evaporation, radiation-based methods, pan evaporation, Switzerland},
-doi = {https://doi.org/10.1002/(SICI)1099-1085(20000215)14:2<339::AID-HYP928>3.0.CO;2-O},
+doi = {10.1002/(SICI)1099-1085(20000215)14:2<339::AID-HYP928>3.0.CO;2-O},
 url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/%28SICI%291099-1085%2820000215%2914%3A2%3C339%3A%3AAID-HYP928%3E3.0.CO%3B2-O},
 eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/%28SICI%291099-1085%2820000215%2914%3A2%3C339%3A%3AAID-HYP928%3E3.0.CO%3B2-O},
 abstract = {Abstract Eight radiation-based equations for determining evaporation were evaluated and expressed in five generalized forms. Five evaporation equations (Abtew, Hargreaves, Makkink, Priestley and Taylor and Turc), where each represents one generalized form, were then compared with pan evaporation measured at Changins station in Switzerland. The comparison was first made using the original constant values involved in each equation, and then using the recalibrated constant values. Evaluation of the Priestley and Taylor equation requires net radiation data as input, in this study, net radiation was estimated using Equation (16) owing to the lack of observation data. The results showed that when the original constant values were used, large errors resulted for most of the equations. When recalibrated constant values were substituted for the original constant values, four of the five equations improved greatly, and all five equations performed well for determining mean annual evaporation. For seasonal and monthly evaporation, the Hargreaves and Turc equations showed a significant bias, especially for cold months. With properly determined constant values, the Makkink and modified Priestley and Taylor equations resulted in monthly evaporation values that agreed most closely with pan evaporation in the study region. The simple Abtew equation can also be used when other meteorological data except radiation are not available. Copyright © 2000 John Wiley \& Sons, Ltd.},
@@ -116,7 +119,7 @@ @article{linacre1977simple
 pages = {409-424},
 year = {1977},
 issn = {0002-1571},
-doi = {https://doi.org/10.1016/0002-1571(77)90007-3},
+doi = {10.1016/0002-1571(77)90007-3},
 url = {https://www.sciencedirect.com/science/article/pii/0002157177900073},
 author = {Edward T. Linacre},
 abstract = {The Penman formula for the evaporation rate from a lake is simplified to the following: E0=700Tm/(100−A)+15(T−Td)(80−T)(mmday−1) where Tm = T + 0.006h, h is the elevation (metres), T is the mean temperature, A is the latitude (degrees) and Td is the mean dew-point. Values given by this formula typically differ from measured values by about 0.3 mm day−1 for annual means, 0.5 mm day−1 for monthly means, 0.9 mm day−1 for a week and 1.7 mm day−1 for a day. The formula applies over a wide range of climates. Monthly mean values of the term (T − Td) can be obtained either from an empirical table or from the following empirical relationship, provided precipitation is at least 5 mm month−1 and (T − Td) is at least 4°C:(T−Td)=0.0023h+0.37T+0.53R+0.35Rann−10.9°C where R is the mean daily range of temperature and Rann is the difference between the mean temperatures of the hottest and coldest months. Thus the evaporation rate can be estimated simply from values for the elevation, latitude and daily maximum and minimum temperatures.}
@@ -188,6 +191,7 @@ @article{abtew1996evapotranspiration
   pages={465--473},
   year={1996},
   publisher={Wiley Online Library}
+  doi={10.1111/j.1752-1688.1996.tb04044.x},
 }
 
 @article{makkink1957testing,
@@ -207,7 +211,7 @@ @article{OUDIN2005290
 pages = {290-306},
 year = {2005},
 issn = {0022-1694},
-doi = {https://doi.org/10.1016/j.jhydrol.2004.08.026},
+doi = {10.1016/j.jhydrol.2004.08.026},
 url = {https://www.sciencedirect.com/science/article/pii/S0022169404004056},
 author = {Ludovic Oudin and Frédéric Hervieu and Claude Michel and Charles Perrin and Vazken Andréassian and François Anctil and Cécile Loumagne},
 keywords = {Rainfall–runoff modelling, Sensitivity analysis, Potential evapotranspiration, Parsimony},
@@ -221,7 +225,7 @@ @article{Danlu2016r
 pages = {216-224},
 year = {2016},
 issn = {1364-8152},
-doi = {https://doi.org/10.1016/j.envsoft.2015.12.019},
+doi = {10.1016/j.envsoft.2015.12.019},
 url = {https://www.sciencedirect.com/science/article/pii/S136481521530133X},
 author = {Danlu Guo and Seth Westra and Holger R. Maier},
 keywords = {Evapotranspiration (ET), Evaporation, Ensemble modelling, R package, Evapotranspiration software},
@@ -236,7 +240,7 @@ @article{miralles2020
 number = {11},
 pages = {e2020WR028055},
 keywords = {evaporation, evapotranspiration, transpiration, interception},
-doi = {https://doi.org/10.1029/2020WR028055},
+doi = {10.1029/2020WR028055},
 url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020WR028055},
 eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR028055},
 note = {e2020WR028055 2020WR028055},
@@ -263,7 +267,7 @@ @article{Yang2018HydrologicIO
   year={2018},
   volume={9},
   pages={44-48},
-  doi={https://doi.org/10.1038/s41558-018-0361-0}
+  doi={10.1038/s41558-018-0361-0}
 }
 
 @book{pyet0_2019, title={PyETo}, url={https://github.com/woodcrafty/PyETo}, author={Richards, Mark}, year={2019}}

pyet/rad_utils.py

@@ -118,24 +118,24 @@ def calc_rad_short(rs=None, tindex=None, lat=None, alpha=0.23, n=None,
     if rs is not None:
         return (1 - alpha) * rs
     else:
-        return (1 - alpha) * calc_rad_sol_in(tindex, lat, n=n, nn=nn)
+        return (1 - alpha) * calc_rad_sol_in(tindex, lat, n, nn=nn)
 
 
-def calc_rad_sol_in(tindex, lat, as1=0.25, bs1=0.5, n=None, nn=None):
+def calc_rad_sol_in(tindex, lat, n, as1=0.25, bs1=0.5, nn=None):
     """Incoming solar radiation [MJ m-2 d-1].
 
     Parameters
     ----------
     tindex: pandas.DatetimeIndex
     lat: float, optional
         the site latitude [rad]
+    n: pandas.Series/float
+        actual duration of sunshine [hour]
     as1: float, optional
         regression constant,  expressing the fraction of extraterrestrial
         reaching the earth on overcast days (n = 0) [-]
     bs1: float, optional
         empirical coefficient for extraterrestrial radiation [-]
-    n: pandas.Series/float, optional
-        actual duration of sunshine [hour]
     nn: pandas.Series/float, optional
         maximum possible duration of sunshine or daylight hours [hour]
 
@@ -148,8 +148,8 @@ def calc_rad_sol_in(tindex, lat, as1=0.25, bs1=0.5, n=None, nn=None):
     Based on equation 35 in [allen_1998]_.
     """
     ra = extraterrestrial_r(tindex, lat)
-    if n is None:
-        n = daylight_hours(tindex, lat)
+    if nn is None:
+        nn = daylight_hours(tindex, lat)
     return (as1 + bs1 * n / nn) * ra
 
 

tests/testmeteo.py

@@ -0,0 +1,16 @@
+import unittest
+
+import numpy as np
+import pandas as pd
+
+import pyet as et
+
+
+class Testmeteo(unittest.TestCase):
+    def test_calc_rad_sol_in(self):
+        # Based on example 10, p 50 TestFAO56
+        tindex = pd.to_datetime("2021-5-15")
+        lat = -22.9 * np.pi / 180
+        n = 7.1
+        rad_sol_in = et.calc_rad_sol_in(tindex, lat, n)
+        self.assertAlmostEqual(float(rad_sol_in), 14.5, 1)